How to better exploit data in projects

Digital transformation is arguably the most significant trend of the past decade, affecting every sector. Even COVID-19’s biggest long-term business impact might end up being the acceleration of digitisation. I dialled in to a recent Project Data Pioneers webinar on seizing the project data opportunity.

Gareth Parkes is Sir Robert McAlpine’s (SRM’s) head of data. He shared insights from his journey to implement a transformational vision around the digitisation of what many people consider a highly physical business.

Parkes was frank about the difficulties in exploiting data around complex and iconic project delivery environments in construction, which operates with tight margins. “Historically we have been poor as an industry at adopting digital technologies,” he said. Data has ended up a neglected asset class.

We can address this problem in two realms, he said. There are factors you can influence – your own attitude to exploiting data; how well trained your team is to gather, analyse and use it; and whether your projects or business are open to taking the right steps. But there is also a second component – actively playing a role in a longer-term, industry-wide way.

That means thinking about data standards in project management more generally and how that might help influence a range of shared outcomes. A great example is the Construction Data Trust, which “allows organisations to share their data in a secure way… to apply advanced analytics and AI to the data and drive transformational change across the industry”.

Start with the needs of individuals

Parkes said there is a balance to strike between internal and external factors when charting the kind of transformation that enhanced data exploitation needs. And it is a transformation – so thinking of this as a programme of projects in itself can help.

“The alignment of needs [between the company, project teams and individuals] is important… but we start with the needs of individuals,” he said. Opening the door to data- and digital-driven efficiencies for project professionals to address personal challenges clears the way for top-down projects built on data.

Early wins are also important. Parkes and his team found a small project team at SRM that needed to migrate legacy data to a new system. “We were able to show you could do it in advanced ways very rapidly,” he said. “That moved us into some business development activities and other areas.”

The insights from the small initial crowdsourcing efforts – including complaints about the rigidity of systems, or the kind of data needed to inform better decisions – helped frame the data team’s opportunities. “We were in a position to demonstrate people wanted change in pockets, then string together the pockets and expand the strategic ambitions,” said Parkes. “It showed there was also a return on investment.”

Two out of 10 on maturity

“Increasingly, we’re also seeing clients wrestle with these challenges,” said Parkes. “On a maturity scale up to 10, we’re perhaps at two in terms of the data quality and volume we need to be connecting.”

And there are other wrinkles to iron out. “For example, there’s a massive challenge around ownership of the data,” Parkes explained. “We’re very collaborative, with teams from lots of different organisations working together. So the way the data is strung together – or not – is a real minefield.

“If the public is paying for a project, how much of the delivery data is owned by the public? If you’re going to build 40 hospitals, how do you show that the 40th build has learned from the projects to build the 39 before it?”

Some caution is needed, however: more open industry and client approaches that sweep up potentially sensitive data could cause commercial and compliance problems.

One route for the SRM programme was to target training around new approaches for data around a cohort of apprentices, despite grappling with the pandemic. “The mindset that we’ve got of being iterative and planning to completely reinvent things as we go [really helped],” said Parkes. “As one of our project data analysts said to me, ‘We’re in uncharted waters and need to roll with the waves at times.’ That’s why we’re now starting to see that pull from the business.”

An example of that pull has been understanding what’s going on at sites during this period when it’s harder to have eyes on activity – which means more detailed data is required. “Another is a rethink of the way we do reporting – looking at improving decision-making, capturing data at a project level, then manipulating the data to make enterprise-level decisions better.”

A tenfold improvement in delivery performance

Emerging applications such as building information modelling (BIM), quantity surveying and commercial management are also benefiting from a more energetic and aligned approach to data. “But what I’m really excited about is combining different skill sets and disciplines –to bring together core disciplines united by this understanding of what they want to do with their data,” Parkes said.

Project leaders looking to focus on data need… data. How it’s generated and formatted are important. But to build a project data programme, management support and money are also key. And that means building an ROI case. “It’s got to be tied back to benefits,” said Parkes. “Measure them – and focus on the projects that will deliver [practical change]. Then you can build roadmaps and skills deployment.”

In other words, it’s that iterative approach of listening to needs; building in training; pushing out data-led solutions; and mapping potential extensions as you go.

And the future? “By applying and pooling advanced data analytics and AI we will be able to facilitate a tenfold improvement in project delivery performance, of benefit not just to the construction industry, but across all project environments,” Parkes said.

That’s a worthwhile aim for what’s shaping up to be an industry-wide iterative process.